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The instructional practices used in introductory college courses often differ dramatically from those used in high school courses, and dissatisfaction with these practices is cited by students as a prominent reason for leaving science, technology, engineering, and mathematics (STEM) majors. To better characterize the transition to college course work, we investigated the extent to which incoming expectations of course activities differ based on student demographic characteristics, as well as how these expectations align with what students will experience. We surveyed more than 1500 undergraduate students in large introductory STEM courses at three research-intensive institutions during the first week of classes about their expectations regarding how class time would be spent in their courses. We found that first-generation and first-semester students predict less lecture than their peers and that class size had the largest effect on student predictions. We also collected classroom observation data from the courses and found that students generally underpredicted the amount of lecture observed in class. This misalignment between student predictions and experiences, especially for first-generation and first-semester college students and students enrolled in large- and medium-size classes, has implications for instructors and universities as they design curricula for introductory STEM courses with explicit retention goals.
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Protocol for Meta-Analyses Examining Personalized Adaptive Learning in Undergraduate Mathematics
This protocol is for a study that examines personalized adaptive learning (PAL) of undergraduate students with a focus on mathematics outcomes. This protocol addresses two meta-analytic studies: 1) Examination of PAL within the population of undergraduate students enrolled in mathematics courses broadly (across all mathematics courses with the type of course as a moderator); and 2) Specifically in college algebra, which is a STEM pipeline mathematics course. Undergraduate mathematics courses can be roadblocks to college degree attainment. PAL offers the opportunity to develop mathematical skills in a personalized way, while enabling instructors to identify students’ struggle areas and take remedial action.Partnering with academic librarians, databases likely to index relevant studies were identified, the search strategy was refined, and keywords and subject indexing terms were identified. Titles and abstracts were independently screened by two reviewers. Full-text review is in progress. Retained studies will have data extracted that will allow the results to be meta-analyzed.The standardized mean difference will be the main effect size computed. Multilevel meta-analysis will be used to address the hierarchical data structure. Robust variance estimation will be used to estimate standard errors and hypothesis tests, addressing dependencies of effect sizes within studies. Prediction intervals for effect sizes, for study-average effect sizes, and heterogeneity statistics will be reported. Subgroup analyses will evaluate the relationship between moderators and the magnitude of the effect size. Cochrane’s criteria for assessing the risk of bias in studies with a separate control group will be applied. Reporting bias will be assessed visually with funnel plots.
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- Award ID(s):
- 2236074
- PAR ID:
- 10563603
- Publisher / Repository:
- Nordic Journal of Systematic Reviews in Education
- Date Published:
- Journal Name:
- Nordic Journal of Systematic Reviews in Education
- Volume:
- 2
- ISSN:
- 2704-1883
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.23865/njsre.v2.6339
